Source CommonsFRAMEWORKBETA
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Communities to build explainable AI from trusted sources

Open source by designExplore communities

Open data sources used by the community

Wikidatadata.govdata.europa.eudata.gouv.frOpen Government CanadaWorld BankWikipediaKaggleHugging FaceGitHubHuwise

Community workspace

Spaces

Urban PlanningESG AnalysisCity/Toronto
SourcesFind source records and evidence.Use casesConnect data work to real needs.ToolsReuse collection and validation tools.Skills.mdDocument reusable workflows.MCP serversExpose shared capabilities.

Urban Planning

Open data for permits, mobility, land use and city services.

12 members4 lists

Climate Adaptation

Risks, infrastructure and local evidence for public planning.

8 members2 models

Public Procurement

Sources, tenders and contract datasets for accountability.

6 members3 lists

Spaces

Build together.

  1. 01

    Identify a need

    Users define the problem to solve.

  2. 02

    Define the model

    Members choose the fields that matter.

  3. 03

    Share the work

    Collection is assigned to contributors.

  4. 04

    Collect information

    Contributors add sources, evidence and context.

  5. 05

    Validate

    An automated validator checks contributions against the selected model.

  6. 06

    Publish

    A reusable dataset is published with its history.

Open spaces

Data lists

Create and share your best data lists

Browse data lists
Best urban planning data sources48 sources126 savesReal Estate Datasets: The list of lists31 sources92 savesBike sharing datasets24 sources76 savesWikidata utilities datasets18 sources61 savesOpen data portals for climate41 sources55 saves
New dataConsensus draft
source_urlRequired
publisherRequired
geographyRequired
licenseRecommended
update_frequencyRecommended
evidence_noteOptional
Browse data models

Data models

Define new data models collectively

Build consensus on which fields you need and how a new dataset should be structured.

Browse data models

Framework

Assemble a dataset together

Start contributing

Add contributors

Assign a perimeter

Validate

Merge in confidence

History
Choose models
Keep the decision
Reverse engineer any change
Document your journey

Traceability

Traceable data transformations

Sources

Start from any source.

Bring the information you already have. Structured data is combined; unstructured material is extracted and shaped into useful fields.

Structured data

  • CSV files
  • APIs
  • Open datasets
  • Data portals
Merge and normalize

Unstructured data

  • PDFs
  • Reports
  • Web pages
  • Text and images
Extract and transform
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Frequently asked questions

What is the Source Commons Framework?

An open source community infrastructure for discovering, documenting, building and reusing unique data sources.

What can a team build?

A team can open a space, gather sources, define a data model, distribute collection tasks and publish reusable datasets.

How are resources structured?

Catalogs connect sources, evaluations, tools, Skills.md and use cases through shared, standards-aligned metadata.

Why does SCF matter for AI uses?

AI systems need structured data, provenance, quality signals and reproducible workflows. SCF keeps those elements explicit and inspectable.

Which portals and repositories are connected?

Discovery paths include data.gouv.fr, data.europa.eu, Open Government Canada, World Bank Data, Wikidata, GitHub, Hugging Face and Kaggle.

How can I contribute?

Create or join a space, add sources and tools, curate data lists or contribute to a shared collection task.

Read the framework glossary